As Figure REF  shown, the samples from Kinetics-400 [1]} are actor-centered while the samples from UCF-Crime [2]} are not [3]}, [4]}. Additionally, the anomalies in frames are usually small and low-resolution. These situations indicate the domain gap between the two kinds of datasets. In this work, we propose MIST to minimize the domain gap by training both feature encoder and classifier in a two stage self-training scheme.
